Image processing involves processing of an image such as a photograph or a video frame to generate a processed image, or a set of characteristics or parameters related to the image as the output of the processing.
The processing of an image may involve various tasks like binarization, page segmentation, skew correction, character recognition, and page layout analysis. These tasks can be accomplished by various conventional known algorithms available in the market. However, a major problem arises in intra image variations wherein a single algorithm may not produce acceptable or desired results. Further, no single algorithm known can process the images well under all conditions.
Moreover, in the conventional approach, an algorithm or a technique, and its corresponding parameters are selected based on user feedback in order to obtain a desired processed image. The major limitation of the conventional approach is that it involves manual intervention which makes the system slow and the final result being sensitive to the human perception. Though there exist various approaches suggesting a suitable algorithm for image processing using machine learning approach, but nevertheless these do not address the challenges faced for intra image variations. Therefore, a need exists for automatically identifying one or more algorithms from a plurality of algorithms, which matches the requirement of an image during processing. Certain embodiments of the present invention are intended to meet these needs and other objectives that will become apparent from the description and drawings set forth below.